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Graph Embedding

Graph embeddings learn a mapping from a network to a vector space, while preserving relevant network properties.

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Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 401–410 of 1192 papers

Title	Date	Tasks	Status	Hype	Score
Faithiful Embeddings for EL++ Knowledge Bases	Jan 24, 2022	Graph EmbeddingKnowledge Graph Embedding	CodeCode Available	0	5
Adversarially Regularized Graph Attention Networks for Inductive Learning on Partially Labeled Graphs	Jun 7, 2021	Graph AttentionGraph Embedding	CodeCode Available	0	5
A Study on Knowledge Graph Embeddings and Graph Neural Networks for Web Of Things	Oct 23, 2023	Graph EmbeddingKnowledge Graph Embedding	CodeCode Available	0	5
From axioms over graphs to vectors, and back again: evaluating the properties of graph-based ontology embeddings	Mar 29, 2023	Graph EmbeddingOntology Embedding	CodeCode Available	0	5
Connector 0.5: A unified framework for graph representation learning	Apr 25, 2023	Graph EmbeddingGraph Generation	CodeCode Available	0	5
DynamicGEM: A Library for Dynamic Graph Embedding Methods	Nov 26, 2018	Dynamic graph embeddingGeneral Classification	CodeCode Available	0	5
Force-directed graph embedding with hops distance	Sep 11, 2023	Graph EmbeddingLink Prediction	CodeCode Available	0	5
From Local to Global: Spectral-Inspired Graph Neural Networks	Sep 24, 2022	Graph Embedding	CodeCode Available	0	5
From Node Embedding To Community Embedding	Oct 31, 2016	Graph EmbeddingNode Classification	CodeCode Available	0	5
Graph Representation Learning via Hard and Channel-Wise Attention Networks	Jul 5, 2019	Graph AttentionGraph Classification	CodeCode Available	0	5

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Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	DeepGG	Entropy Difference	0	—	Unverified